class_docstr: ARLSTem stemmer : a light Arabic Stemming algorithm without any dictionary.
  Department of Telecommunication & Information Processing. USTHB University,
  Algiers, Algeria.
  ARLSTem.stem(token) returns the Arabic stem for the input token.
  The ARLSTem Stemmer requires that all tokens are encoded using Unicode
  encoding.
class_docstr_tok: ["ARLSTem","stemmer",":","a","light","Arabic","Stemming","algorithm","without","any","dictionary",".","Department","of","Telecommunication","&","Information","Processing",".","USTHB","University",",","Algiers",",","Algeria",".","ARLSTem.stem","(","token",")","returns","the","Arabic","stem","for","the","input","token",".","The","ARLSTem","Stemmer","requires","that","all","tokens","are","encoded","using","Unicode","encoding","."]
docstr: stem the present prefixes
docstr_tok: ["stem","the","present","prefixes"]
code: def verb_t4(self, token):
      """
      stem the present prefixes
      """
      if len(token) > 3:
          for pr1 in self.verb_suf1:
              if token.startswith(pr1):
                  return token[1:]
          if token.startswith("\u064A"):
              return token[1:]
  
file_path: nltk/nltk/stem/arlstem.py
imports: import re
  from nltk.stem.api import StemmerI
label_desc: Use image node_id 12 for calling the ARLSTem obj's underlying member method code with example usage: obj.verb_t4(token) and returns: token, token